The Accent of Feature Drift: Where Reconstruction Error Is Not Noise

Reconstruction trajectories provide a readout of how diffusion architectures organize internal features. We study feature drift, the per-layer discrepancy between a reconstruction trajectory and an independently sampled forward reference of the same image, and define the architecture accent as its min–max normalized depth profile. Under a specified readout protocol, the accent is reproducible across tested variants within trained lineages and varies across architectures. Ten model instances spanning five backbone families exhibit two dominant forms, interior-localized and terminal-ramp, with a terminal-spike boundary in two further lineages. The dominant classes are recovered in leave-one-out evaluation within this registry. These forms have different measurement interpretations: terminal ramps largely track the reference features' norm schedule and lose their ramp label under relative L2, whereas the tested interior-localized profiles retain peaks before the final block under norm-free metrics. Controlled interventions show that drift magnitude does not uniquely determine reconstruction quality, and that site sensitivity in training-free correction differs across architectures. Random-initialization controls and retraining under two objectives further indicate that the observed organization develops with training. Together, these results show how reconstruction trajectories can be used to read out architectural organization and identify candidate sites for training-free correction.